This invention relates to apparatus for validating items of value, particularly currency articles, and to methods of configuring such apparatus. The invention will be described in the context of coin validators, but is also applicable to banknote validators and validators for other items of value.
It is well known to take measurements of coins and apply acceptability tests to determine whether the coin is valid and the denomination of the coin. The acceptability tests are normally based on stored acceptability data. One common technique (see, e.g. GB-A-1 452 740) involves storing “windows”, i.e. upper and lower limits for each test. If each of the measurements of a coin falls within a respective set of upper and lower limits, then the coin is deemed to be acceptable. The acceptability data could instead represent a predetermined value such as a mean, the measurements then being tested to determine whether they lie within predetermined ranges of that value. Alternatively, the acceptance data could be a look-up table which is addressed by the measurements, and the output of which indicates whether the measurements are suitable for a particular denomination (see, e.g. EP-A-0 480 736, and U.S. Pat. No. 4,951,799). Instead of having separate acceptance criteria for each test, the measurements may be combined and the result compared with stored acceptance data (cf. GB-A-2 238 152 and GB-A-2 254 949). Alternatively, some of these techniques could be combined, e.g. by using the acceptability data as coefficients (derived, e.g. using a neural network technique) for combining the measurements, and possibly for performing a test on the result.
The acceptability data can be derived in a number of different ways. For example, each validator can be calibrated by feeding many items into the validator and acquiring test measurements of the items. The acceptance data is then derived from the test measurements, and takes account of the individual sensor response characteristics of the validator; accordingly the acceptability data will vary from validator to validator. Another technique may involve deriving the acceptability data using a standard machine (which may in practice be a nominal machine, the data being derived by statistical analysis of test measurements performed in a group of machines of similar construction, or at least having sensor arrangements of similar construction.). This acceptance data can then be transferred to production validators. If individual differences within the validators require that they be individually calibrated, then the acceptance data could be modified, for example using the techniques described in GB-A-2 199 978.
It is also known for validators to have an automatic re-calibration function, sometimes known as “self-tuning”, whereby the acceptance data is regularly updated on the basis of measurements performed during testing (see for example EP-A-0 155 126, GB-A-2 059 129, and U.S. Pat. No. 4,951,799).
It is sometimes desirable to re-configure an existing validator in the field (c.f. GB-A-2 199 978 and WO-A-96/07992). For example, if the validator is arranged to validate a certain range of denominations it may be desired to add a different denomination to that range, or to substitute one of those denominations for a different one. However, it is desirable to avoid the need to perform a very large number of tests in order to calibrate the validator for the new denomination.